Life Sciences and Analytics SAS 2.0

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1 Life Sciences and Analytics SAS 2.0 Dave Handelsman Business Solutions Manager, SAS

2 Life Sciences and Analytics SAS 1.0 Capture data Raw data sets Develop, test and apply SAS programs Extracted data sets Develop, test and apply SAS programs Analysis data sets Develop, test and apply SAS programs Statistical results Import results into MS-Word Clinical study report 2

3 Principles Guiding SAS Health and Life Sciences 1. The health and life sciences ecosystem is broken. 2. Deeper insights into patients and organizations are needed to improve it. 3. These insights will come from a new era of industry analytics. 4. These analytics will rely on data found all across the ecosystem. 3

4 The SAS Health and Life Sciences Strategy Vision: SAS will be the compliant, integrated platform on which the health and life sciences industries derive scientific and business insight. Fundamental Belief: The future innovations in healthcare, health plans, and life sciences will be powered by information shared across these historically distinct market segments with convergence around patient data. 4

5 Life Sciences R&D Moving Into The Future Portfolio Optimization Hierarchical set of business capabilities Consistent information chain for decisionmaking Power of analytics at one level can be leveraged by analytics at other levels Base SAS Performance Management Safety and Signal Detection Clinical Integration & Standards Clinical Statistics Data Repository Compliance

6 SAS Drug Development An integrated system for developing, managing, validating, and reviewing SAS reports and analyses within and across research studies Controls and compliance Centralized information management and processing Collaborative access to address: Safety and efficacy reporting Inclusion of statistical results in study reports and submissions Ad hoc data exploration by scientists Clinical Statistics Data repository Compliance 6

7 SAS Drug Development Adoption 7

8 Clinical Data Integration and Standards The business problem Factors Impacts Results Disparate data Inaccurate data Incomplete data Poorly timed data Multiple versions of the truth Wasted effort Poor relationships (CRO, lab, etc.) Trial delays Inaccurate information for management Bad decisions Lost revenue Lost productivity Lost market opportunity Clinical Integration & Standards 8

9 Clinical Data Integration and Standards CDISC (Clinical Data Interchange Standards Consortium) The CDISC mission is to develop and support global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of healthcare. 9

10 Clinical Data Integration and Standards SAS and CDISC SAS is actively engaged at multiple levels with CDISC Ed Helton: Chairman, Board of Directors Dave Handelsman: Industry Advisory Board Ann-Sofie Bergstrom: European Coordinating Committee Charter (E3C) Representatives on multiple modeling committees - ODM - SDTM - ADaM - Protocol Representation - CRT-DDS (define.xml) Active involvement in FDA pilots 10

11 Clinical Data Integration and Standards SAS and CDISC SAS Clinical Standards Toolkit SAS Clinical Data Integration 11

12 Clinical Data Integration and Standards SAS Clinical Toolkit Provides SDTM validation define.xml (CRT-DDS) creation Will ultimately include functionality beyond CDISC Will be available for no additional license fees beyond SAS/Base licensing 12

13 Clinical Data Integration and Standards SAS Clinical Data Integration Solution Enterprise data integration strategy vs. code that satisfies one integration scenario A set of automated, repeatable, managable processes An end to end, metadata driven data integration platform Data standardization Data cleansing Data quality Master data management Pre-built support for CDISC Extensible to other standards Integrates disparate systems 13

14 How is Drug Safety done today? Not timely, manual, inconsistent, non-standard For pre-approval analyses Every company uses SAS to perform similar analyses Every company uses SAS differently to perform similar analyses For post-approval analyses, ad hoc tools and processes are used Safety and Signal Detection 14

15 What s different in 2008? New regulations and guidelines New Safety Guidances Pre and Post Approval Adverse Event Reporting Improving Subject Protection Drug Safety Information FDA s Communication to the Public FDA Good Review Practice / Clinical Review Template Conducting a Clinical Safety Review of a New Product Application and Preparing a Report on the Review 15

16 What s different in 2008? Customer tools are dated Do not address new FDA guidances and practices Ad hoc only for advanced analytics Industry data standards (CDISC) are being implemented Standard data leads to standard reports 16

17 What s different in 2008? SAS has packaged capabilities that Address new safety guidances Provide pharmacovigilance / signal detection Enable comprehensive safety management These capabilities are part of a SAS platform offering that can address these and more issues 17

18 SAS Integrated Capabilities for Life Sciences Data standardization plus Safety SAS Clinical Data Int. Data standardization, repository plus Safety SAS Patient Safety Repository, strong compliance plus Safety SAS Drug Development

19 SAS Performance and Portfolio Management Represent longer-term investments Existing horizontal capabilities today Will leverage multiple sources of information within analytics Clinical Financial Market research Sales Safety Portfolio Optimization Performance Management Bottom up and Top down views of the business 19

20 SAS Performance and Portfolio Management Operational questions to answer How is study x performing? Recruitment Financially Etc. How should study x be performed? Strategic questions to answer Balancing predicted revenue vs. risk Where should we invest? Where should we stop investing? Portfolio Optimization Performance Management 20

21 SAS Beyond Life Sciences R&D Manufacturing SAS Demand Forecasting for Pharmaceutical Manufacturing Sales and Marketing Maximizing the efficiency of sales and marketing spending Analytics can optimize: Size, allocation and deployment of sales representatives Key factors that drive prescriber behavior Promotional mix (sales calls, e-detailing, samples, etc) 21

22 The Power of a Comprehensive Platform Example: Patient Safety Ask better questions; get better answers Standardize and automate Align to regulators 24

23 SAS Highlights at PharmaSUG 2008 Name Title Day / Time Pete Villiers SAS, CDISC and Clinical Data Integration M 8:30 Dan Heath Effective Graphics Made Simple Using SAS/GRAPH SG Procedures M 9:30 David Duling From Soup to Nuts: Practices in Data Management for Analytical Performance M 11:00 Maura Stokes New SAS Statistical Software: Just Over the Horizon M 1:30 Tony Friebel Power up XML with SAS M 2:30 Dawn Hopper SAS Certification: Are You Ready to Put Your SAS Skills to the Test? M 4:00 Cynthia Zender Creating Complex Reports T 8:00 Teresia Arthur Web-Enable Your SAS Applications T 9:30 Tips and Tricks for Creating Multi-Sheet Microsoft Excel Workbooks the Vince DelGobbo Easy Way with SAS T 1:30 Maura Stokes An Introduction to SAS Stat Studio for SAS/STAT Users T 3:30 David Olaleye Automated Drug Safety Signal Detection with Guided Analysis W 8:30 Industry+SAS Panel Discussion: Regulatory Submissions and CDISC Standards W 10:00 Elizabeth Ceranowski SAS Abbreviations are your friends, use a template method to code! W 11:00 25

24 SAS Highlights at PharmaSUG 2008 SuperDemos In the exhibit hall at scheduled times throughout the conference SAS Certification Preparation at Your Fingertips SAS and JMP Integration Featuring JMP Genomics You Want ME to use Enterprise Guide?? Techniques for Writing SAS Programs in SAS Drug Development SAS/Graph; Graph Template Language SAS Stat Studio SAS, CDISC and Data Integration Studio Interactive Patient Safety Exploration 26

25 The SAS Health and Life Sciences Strategy SAS will be the compliant, integrated platform on which the health and life sciences industries derive scientific and business insight. Portfolio Optimization Performance Management Safety and Signal Detection Clinical Integration & Standards Clinical Statistics Data Repository Compliance Base SAS 27

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